102,674 research outputs found
SEARS: Space Efficient And Reliable Storage System in the Cloud
Today's cloud storage services must offer storage reliability and fast data
retrieval for large amount of data without sacrificing storage cost. We present
SEARS, a cloud-based storage system which integrates erasure coding and data
deduplication to support efficient and reliable data storage with fast user
response time. With proper association of data to storage server clusters,
SEARS provides flexible mixing of different configurations, suitable for
real-time and archival applications.
Our prototype implementation of SEARS over Amazon EC2 shows that it
outperforms existing storage systems in storage efficiency and file retrieval
time. For 3 MB files, SEARS delivers retrieval time of s compared to
s with existing systems.Comment: 4 pages, IEEE LCN 201
Computing in the RAIN: a reliable array of independent nodes
The RAIN project is a research collaboration between Caltech and NASA-JPL on distributed computing and data-storage systems for future spaceborne missions. The goal of the project is to identify and develop key building blocks for reliable distributed systems built with inexpensive off-the-shelf components. The RAIN platform consists of a heterogeneous cluster of computing and/or storage nodes connected via multiple interfaces to networks configured in fault-tolerant topologies. The RAIN software components run in conjunction with operating system services and standard network protocols. Through software-implemented fault tolerance, the system tolerates multiple node, link, and switch failures, with no single point of failure. The RAIN-technology has been transferred to Rainfinity, a start-up company focusing on creating clustered solutions for improving the performance and availability of Internet data centers. In this paper, we describe the following contributions: 1) fault-tolerant interconnect topologies and communication protocols providing consistent error reporting of link failures, 2) fault management techniques based on group membership, and 3) data storage schemes based on computationally efficient error-control codes. We present several proof-of-concept applications: a highly-available video server, a highly-available Web server, and a distributed checkpointing system. Also, we describe a commercial product, Rainwall, built with the RAIN technology
Applications of atomic ensembles in distributed quantum computing
Thesis chapter. The fragility of quantum information is a fundamental constraint faced by anyone trying to build a quantum computer. A truly useful and powerful quantum computer has to be a robust and scalable machine. In the case of many qubits which may interact with the environment and their neighbors, protection against decoherence becomes quite a challenging task. The scalability and decoherence issues are the main difficulties addressed by the distributed model of quantum computation. A distributed quantum computer consists of a large quantum network of distant nodes - stationary qubits which communicate via flying qubits. Quantum information can be transferred, stored, processed and retrieved in decoherence-free fashion by nodes of a quantum network realized by an atomic medium - an atomic quantum memory. Atomic quantum memories have been developed and demonstrated experimentally in recent years. With the help of linear optics and laser pulses, one is able to manipulate quantum information stored inside an atomic quantum memory by means of electromagnetically induced transparency and associated propagation phenomena. Any quantum computation or communication necessarily involves entanglement. Therefore, one must be able to entangle distant nodes of a distributed network. In this article, we focus on the probabilistic entanglement generation procedures such as well-known DLCZ protocol. We also demonstrate theoretically a scheme based on atomic ensembles and the dipole blockade mechanism for generation of inherently distributed quantum states so-called cluster states. In the protocol, atomic ensembles serve as single qubit systems. Hence, we review single-qubit operations on qubit defined as collective states of atomic ensemble. Our entangling protocol requires nearly identical single-photon sources, one ultra-cold ensemble per physical qubit, and regular photodetectors. The general entangling procedure is presented, as well as a procedure that generates in a single step Q-qubit GHZ states with success probability p(success) similar to eta(Q/2), where eta is the combined detection and source efficiency. This is signifcantly more efficient than any known robust probabilistic entangling operation. The GHZ states form the basic building block for universal cluster states, a resource for the one-way quantum computer
A Class of MSR Codes for Clustered Distributed Storage
Clustered distributed storage models real data centers where intra- and
cross-cluster repair bandwidths are different. In this paper, exact-repair
minimum-storage-regenerating (MSR) codes achieving capacity of clustered
distributed storage are designed. Focus is given on two cases: and
, where is the ratio of the available cross- and
intra-cluster repair bandwidths, is the total number of distributed nodes
and is the number of contact nodes in data retrieval. The former represents
the scenario where cross-cluster communication is not allowed, while the latter
corresponds to the case of minimum cross-cluster bandwidth that is possible
under the minimum storage overhead constraint. For the case, two
types of locally repairable codes are proven to achieve the MSR point. As for
, an explicit MSR coding scheme is suggested for the
two-cluster situation under the specific condition of .Comment: 9 pages, a part of this paper is submitted to IEEE ISIT201
Infocast: A New Paradigm for Collaborative Content Distribution from Roadside Units to Vehicular Networks Using Rateless Codes
In this paper, we address the problem of distributing a large amount of bulk
data to a sparse vehicular network from roadside infostations, using efficient
vehicle-to-vehicle collaboration. Due to the highly dynamic nature of the
underlying vehicular network topology, we depart from architectures requiring
centralized coordination, reliable MAC scheduling, or global network state
knowledge, and instead adopt a distributed paradigm with simple protocols. In
other words, we investigate the problem of reliable dissemination from multiple
sources when each node in the network shares a limited amount of its resources
for cooperating with others. By using \emph{rateless} coding at the Road Side
Unit (RSU) and using vehicles as data carriers, we describe an efficient way to
achieve reliable dissemination to all nodes (even disconnected clusters in the
network). In the nutshell, we explore vehicles as mobile storage devices. We
then develop a method to keep the density of the rateless codes packets as a
function of distance from the RSU at the desired level set for the target
decoding distance. We investigate various tradeoffs involving buffer size,
maximum capacity, and the mobility parameter of the vehicles
Coordination-Free Byzantine Replication with Minimal Communication Costs
State-of-the-art fault-tolerant and federated data management systems rely on fully-replicated designs in which all participants have equivalent roles. Consequently, these systems have only limited scalability and are ill-suited for high-performance data management. As an alternative, we propose a hierarchical design in which a Byzantine cluster manages data, while an arbitrary number of learners can reliable learn these updates and use the corresponding data.
To realize our design, we propose the delayed-replication algorithm, an efficient solution to the Byzantine learner problem that is central to our design. The delayed-replication algorithm is coordination-free, scalable, and has minimal communication cost for all participants involved. In doing so, the delayed-broadcast algorithm opens the door to new high-performance fault-tolerant and federated data management systems. To illustrate this, we show that the delayed-replication algorithm is not only useful to support specialized learners, but can also be used to reduce the overall communication cost of permissioned blockchains and to improve their storage scalability
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